[Python-Dev] bpo-34837: Multiprocessing.Pool API Extension (original) (raw)

[Python-Dev] bpo-34837: Multiprocessing.Pool API Extension - Pass Data to Workers w/o Globals

Sean Harrington seanharr11 at gmail.com
Sat Sep 29 08:13:19 EDT 2018

On Sat, Sep 29, 2018 at 6:24 AM Antoine Pitrou <solipsis at pitrou.net> wrote:

Hi Sean, On Fri, 28 Sep 2018 19:23:06 -0400 Sean Harrington <seanharr11 at gmail.com> wrote: > My simple argument is that the > developer should not be constrained to make the objects passed globally > available in the process, as this MAY break encapsulation for large > projects. IMHO, global variables don't break encapsulation if they remain private to the module where they actually play a role. Of course, there are also global-like alternatives to globals, such as class attributes... The multiprocessing module itself uses globals (or quasi-globals) internally for various implementation details.

Yes, class attributes are a viable alternative. I've written about this here. <https://thelaziestprogrammer.com/python/multiprocessing-pool-a-global-solution> Still, the argument is not against global variables, class attributes or any close cousins -- it is simply that developers shouldn't be forced to use these.

> 3. If you don't like globals, you could probably do something like > > lazily-initialize the resource when a function needing it is executed; > > this also avoids creating the resource if the child doesn't use it at > > all. Would that work for you? > > > > I have nothing against globals, my gripe is with being enforced to use > them for every Pool use case. Further, if initializing the resource is > expensive, we only want to do this ONE time per worker process.

That's what I meant with lazy initialization: initialize it if not already done, otherwise just use the already-initialized resource. It's a common pattern. (you can view it as a 1-element cache if you prefer)

Sorry - I wasn't following your initial suggestion. This is a valid solution for ONE of the general use cases (where we initialize objects in each worker post-fork). However it fails for the other Pool use case of "initializing a big object in your parent, and passing to each worker, without using globals."

> As a more general remark, I understand the desire to make the Pool > > object more flexible, but we can also not pile up features until it > > satisfies all use cases. > > > > I understand that this is a legitimate concern, but this is about API > approachability. Python end-users of Pool are forced to declare a global > from a lexical scope. Most Python end-users probably don't even know this > is possible.

Hmm... We might have a disagreement on the target audience of the multiprocessing module. multiprocessing isn't very high-level, I would expect it to be used by experienced programmers who know how to mutate a global variable from a lexical scope.

It is one thing to MUTATE a global from a lexical scope. No gripes there. The specific concept I'm referencing here, is "DECLARING a global variable, from within a lexical scope". This is not as a intuitive for most programmers.

For non-programmer end-users, such as data scientists, there are higher-level libraries such as Celery (http://www.celeryproject.org/) and Dask distributed (https://distributed.readthedocs.io/en/latest/). Perhaps it would be worth mentioning them in the documentation.

We likely do NOT have disagreements on the multiprocessing module. Multiprocessing is NOT high-level, I agree. But the beauty of the "Pool" API is that it gives non-programmer end-users (like data scientists) the ability to leverage multiple cores, without (in most cases) needing to know implementation details about multiprocessing. All they need to understand is the higher-order-function "map()", which is a very simple concept. (I even sound over-complicated myself calling it a "higher-order-function"...)

Regards

Antoine.

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